Quantifying knee-stability mechanics, especially under physiological loading conditions (i.e., time-varying multiple-muscle loads), is critical to understanding the broader aspects of multiple muscle contributions in light of knee ligament failure. The focus of this research is to develop a computational model verified by a sophisticated cadaver-robotic setup to investigate the how knee ligament strain, tibial movement, and intersegmental forces are affected by time-varying muscle loads in synchronous dynamic postures in both ACL impaired and un-impaired knees. The long-term aim is to gain further understanding of the means and extent to which functional ACL-Deficient (ACL-D) subjects reduce associated ligament strain. Quantitative measurements on cadaver ligament strain will be performed as part of the larger effort to quantify knee stability. Synergistic experimental and computational methods will be implemented and lead to the development of (1) an experimental apparatus and procedure to mimic in-vivo knee loading conditions, and (2) a graphical-computational knee model verified by experimental data. These incorporate existing data from human-motion studies, a robot-cadaver experimental set-up, and computational modeling. Previous human-motion studies will provide the data for both the experimental and computational approaches. Both approaches will quantify ligament strain and joint stability parameters. Statistical comparisons between the robot-cadaver and computational model will be used to assess and refine the model. Once verified, the model can be used to investigate other knee [instability parameters and ACL-D muscle recruitment. This proposal outlines the first steps toward establishing a quantitative model for assessment of ligament strain, especially as it relates to subjects with ACL injuries and who have modified their muscle recruitment strategy to remain fully functional. Understanding of such mechanisms could lead to non-surgical physical therapy interventions and thus reduce the need for a surgical intrusion. [unreadable] [unreadable] [unreadable]